Knowledge Discovery from Sensor DataAuroop R. Ganguly, Joao Gama, Olufemi A. Omitaomu, Mohamed Gaber, Ranga Raju Vatsavai As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures. This book presents innovative solutions in offline data mining and real-time |
Contents
Chapter 1 A Probabilistic Framework for Mining Distributed Sensory Data Under Data Sharing Constraints | 1 |
Chapter 2 A General Framework for Mining Massive Data Streams | 9 |
Chapter 3 A Sensor Network Data Model for the Discovery of SpatioTemporal Patterns | 15 |
| 35 | |
| 55 | |
Chapter 6 Anomaly Detection in Transportation Corridors Using Manifold Embedding | 81 |
Chapter 7 Fusion of Vision Inertial Data for Automatic Georeferencing | 107 |
| 131 | |
Chapter 9 Missing Event Prediction in Sensor Data Streams Using Kalman Filters | 149 |
Chapter 10 Mining Temporal Relations in Smart Environment Data Using TempAl | 171 |
| 205 | |
Back cover | 217 |
Other editions - View all
Knowledge Discovery from Sensor Data Auroop R Ganguly,Joao Gama,Ranga Raju Vatsavai,Olufemi a Omitaomu,Mohamed Gaber No preview available - 2019 |
Knowledge Discovery from Sensor Data Auroop R. Ganguly,Joao Gama,Olufemi A. Omitaomu,Mohamed Gaber,Ranga Raju Vatsavai No preview available - 2008 |
Common terms and phrases
accuracy ACM Press activities adaptive algorithm analysis anomaly detection applications approach approximation Artificial Intelligence b-frame clustering streaming clustering structure Computer Science constraints context correlation data mining data streams databases datasets distributed data domain dynamic e-frame edge electrical network Equation error estimate example Figure framework fusion global growing hotspots histograms IEEE inertial input International Conference ISOMAP Kalman filter KF operator Knowledge Discovery linear Machine Learning matrix MavHome METAR methods monitoring navigation network load neural networks nonlinear observations obtained optimization outliers packets parameters patterns PCAg performance points prediction principal components problem Proceedings processing query routing tree sampling sensor data sensor nodes smart environment smart home Spatio-Temporal Sensor Graph Spectral dimension statistics streaming sensors STSG synthetic techniques Technology TempAl temporal relations topology total number transformation University University of Porto update variables vector vehicle vision system wavelets wireless sensor networks